Constructing good deals in discrete time arbitrage-free dynamic pricing models

Recent literature has proved that many classical pricing models (Black and Scholes, Heston, etc.) and risk measures (V aR, CV aR, etc.) may lead to “pathological meaningless situations”, since traders can build sequences of portfolios whose risk leveltends to −infinity and whose expected return tends to +infinity, i.e., (risk = −infinity, return = +infinity). Such a sequence of strategies may be called “good deal”. This paper focuses on the risk measures V aR and CV aR and analyzes this caveat in a discrete time complete pricing model. Under quite general conditions the explicit expression of a good deal is given, and its sensitivity with respect to some possible measurement errors is provided too. We point out that a critical property is the absence of short sales. In such a case we first construct a “shadow riskless asset” (SRA) without short sales and then the good deal is given by borrowing more and more money so as to invest in the SRA. It is also shown that the SRA is interested by itself, even if there are short selling restrictions.

Next Generation of Energy Residential Gateways for Demand Response and Dynamic Pricing

Predictions about electric energy needs, based on current electric energy models, forecast that the global energy consumption on Earth for 2050 will double present rates. Using distributed procedures for control and integration, the expected needs can be halved. Therefore implementation of Smart Grids is necessary. Interaction between final consumers and utilities is a key factor of future Smart Grids. This interaction is aimed to reach efficient and responsible energy consumption. Energy Residential Gateways (ERG) are new in-building devices that will govern the communication between user and utility and will control electric loads. Utilities will offer new services empowering residential customers to lower their electric bill. Some of these services are Smart Metering, Demand Response and Dynamic Pricing. This paper presents a practical development of an ERG for residential buildings.

Active Learning and Dynamic Pricing Policies

In this paper, we address the problem of dynamic pricing to optimize the revenue coming from the sales of a limited inventory in a finite time-horizon. A priori, the demand is assumed to be unknown. The seller must learn on the fly. We first deal with the simplest case, involving only one class of product for sale. Furthermore the general situation is considered with a finite number of product classes for sale. In particular, a case in point is the sale of tickets for events related to culture and leisure; in this case, typically the tickets are sold months before the event, thus, uncertainty over actual demand levels is a very a common occurrence. We propose a heuristic strategy of adaptive dynamic pricing, based on experience gained from the past, taking into account, for each time period, the available inventory, the time remaining to reach the horizon, and the profit made in previous periods. In the computational simulations performed, the demand is updated dynamically based on the prices being offered, as well as on the remaining time and inventory. The simulations show a significant profit over the fixed-price strategy, confirming the practical usefulness of the proposed strategy. We develop a tool allowing us to test different dynamic pricing strategies designed to fit market conditions and seller s objectives, which will facilitate data analysis and decision-making in the face of the problem of dynamic pricing.

Pricing of Product Variants

Työn tutkimusongelma oli selventää, tutkia ja analysoida dynaamisen hinnoittelun tekijät ja mahdollisuudet tuotevarianttien hinnoittelussa. Tutkimusongelman selvittämiseksi työlle asetettiin 8 tavoitetta - Saada selville miksi tuotevarianttien hinnoittelu on ongelmallista - Esittää kuinka tuotevarianttien hinnat teoreettisesti tulisi asettaa - Tunnistaa tuotevarianttien hinnoittelun ulottuvuudet ja selvittää dynaamisen hinnoittelun edut staattiseen hinnoitteluun verrattuna - Esitellä analyysikehikko hinnoittelun tilan analysointiin - Tunnistaa dynaamisen hinnoittelun tuotevarianteille suomat mahdollisuudet - Etsiä soveltuvat hinnoittelumenetelmät tuotevarianttien dynaamiseen hinnoitteluun - Analysoida tuotevariantteja myyvän yrityksen hinnoittelu - Tunnistaa ja arvioida dynaamisen hinnoittelun edut yritykselle Diplomityössä käytettiin useita tutkimusmenetelmiä. Perustieto haettiin kirjallisuustutkimuksella ja sitä täydennettiin haastatteluilla. Tutkimusprosessi alkoi tutkimuksella tuotevarianttien hinnoittelusta ja kirjallisuuden perusteella luotiin näkökulma ja yleiset kehityssuunnat tarkempaa tutkimusta varten. Kaksi tärkeintä tuotevariaatioiden hinnoitteludimensiota tunnistettiin ja niiden analysointia varten luotiin nelikenttämalli. Kirjallisuustutkimuksen ja tarkemman kohdeyrityksen tarkastelun perusteella dynaaminen tuotelinjahinnoittelu on tuotevarianttien dynaamisen hinnoittelun tavoitetila. Nelikenttämallia käytettiin kohdeyrityksen hinnoittelun tilan arviointiin ja dynaamisen hinnoittelun suurimmat hyödyt löydettiin. Tutkimuksen päätulokset ovat - Hinnoittelun dynaamisuutta tulee tuotevarianteilla tutkia hinnoittelun älykkyyden ja kehittyneisyyden kanssa - Tuotevariaatioiden hinnoittelun tavoitetila on dynaaminen tuotelinjahinnoittelu - Hinnoittelun kehittäminen staattisesta dynaamiseen tuo huomattavia etuja - Tärkein etu on parempi hintojen hallinta ja mahdollisuus johtaa hintoja tehokkaasti. Tämän vuoksi hinnoitteluanalyysissa havaittiin selvästi lisääntyneitä voittoja - Hinnoittelun älykkyyden nostaminen hyödyttää yritystä ja saa aikaan lisäyksen voitoissa

Investigating preferences for dynamic electricity tariffs: the effect of environmental and system benefit disclosure

Dynamic electricity pricing can produce efficiency gains in the electricity sector and help achieve energy policy goals such as increasing electric system reliability and supporting renewable energy deployment. Retail electric companies can offer dynamic pricing to residential electricity customers via smart meter-enabled tariffs that proxy the cost to procure electricity on the wholesale market. Current investments in the smart metering necessary to implement dynamic tariffs show policy makers’ resolve for enabling responsive demand and realizing its benefits. However, despite these benefits and the potential bill savings these tariffs can offer, adoption among residential customers remains at low levels. Using a choice experiment approach, this paper seeks to determine whether disclosing the environmental and system benefits of dynamic tariffs to residential customers can increase adoption. Although sampling and design issues preclude wide generalization, we found that our environmentally conscious respondents reduced their required discount to switch to dynamic tariffs around 10% in response to higher awareness of environmental and system benefits. The perception that shifting usage is easy to do also had a significant impact, indicating the potential importance of enabling technology. Perhaps the targeted communication strategy employed by this study is one way to increase adoption and achieve policy goals.

Coordinated Lot-sizing and Dynamic Prizing under a Supplier All-units Quantity Discount

We consider an economic order quantity model where the supplier offers an all-units quantity discount and a price sensitive customer demand. We compare a decentralized decision framework where selling price and replenishment policy are determined independently to simultaneous decision making. Constant and dynamic pricing are distinguished. We derive structural properties and develop algorithms that determine the optimal pricing and replenishment policy and show how quantity discounts not only influence the purchasing strategy but also the pricing policy. A sensitivity analysis indicates the impact of the fixed-holding cost ratio, the discount policy, and the customers' price sensitivity on the optimal decisions.

Coordinated pricing and inventory management

This dissertation mainly focuses on coordinated pricing and inventory management problems, where the related background is provided in Chapter 1. Several periodic-review models are then discussed in Chapters 2,3,4 and 5, respectively. Chapter 2 analyzes a deterministic single-product model, where a price adjustment cost incurs if the current selling price is changed from the previous period. We develop exact algorithms for the problem under different conditions and find out that computation complexity varies significantly associated with the cost structure. %Moreover, our numerical study indicates that dynamic pricing strategies may outperform static pricing strategies even when price adjustment cost accounts for a significant portion of the total profit. Chapter 3 develops a single-product model in which demand of a period depends not only on the current selling price but also on past prices through the so-called reference price. Strongly polynomial time algorithms are designed for the case without no fixed ordering cost, and a heuristic is proposed for the general case together with an error bound estimation. Moreover, our illustrates through numerical studies that incorporating reference price effect into coordinated pricing and inventory models can have a significant impact on firms' profits. Chapter 4 discusses the stochastic version of the model in Chapter 3 when customers are loss averse. It extends the associated results developed in literature and proves that the reference price dependent base-stock policy is proved to be optimal under a certain conditions. Instead of dealing with specific problems, Chapter 5 establishes the preservation of supermodularity in a class of optimization problems. This property and its extensions include several existing results in the literature as special cases, and provide powerful tools as we illustrate their applications to several operations problems: the stochastic two-product model with cross-price effects, the two-stage inventory control model, and the self-financing model.

Tuottojohtamisen mallit ja soveltamistavat teollisuusyrityksissä

Työssä käsitellään tuottojohtamisessa laajasti käytettyjä malleja talouden näkökulmasta. Tarkoituksena on käydä läpi erilaisia malleja, joiden avulla tuottojohtamista voidaan käsitellä ja soveltaa teollisuusyrityksiin. Tavoitteena on luoda yleinen käsitys siitä, mitä eri tuottojohtamisen malleja käsitellään kirjallisuudessa ja miten niitä sovelletaan erilaisissa teollisuusyrityksissä. Monia tuottojohtamisen käsitteitä käytetään hinnoittelussa kuten hintadiskriminointia. Tuottojohtamista voidaan soveltaa monenlaisiin yrityksiin ja aloihin. Eri teollisuuden alojen yhteyttä tuottojohtamiseen tutkitaan niille ominaisten piirteiden kautta keskittyen verkoston tuottojohtamiseen. Työssä keskitytään teollisuusyritysten sovelluksiin. Tuottojohtamisen soveltaminen teollisuudessa on aloitettu vasta lähiaikoina. Käyttökohteita on löytynyt verkoston tuottojohtamisessa.

Sähkönmyyntiyhtiöiden riskienhallinnan haasteet ja kehittäminen

Diplomityön tavoitteena on esitellä sähkökaupan ja erityisesti sähköyhtiöiden kokemia sähkönmyynnin riskejä sekä kuvata sähkönmyyntiin liittyvää riskienhallinnan problematiikkaa. Tarkastelun näkökulmana on tietojärjestelmien ja saatavissa olevan tiedon hyödyntäminen energiayhtiöiden riskienhallinnassa. Toinen päätavoitteista on tutkia, kuinka saatavilla olevaa tiedon hyödyntämistä voidaan kehittää sähkönmyynnin hinnoittelussa sekä suojausten suunnittelussa. Työ toteutettiin työskentelemällä asiantuntijana energia-alaan keskittyneessä ohjelmistoyrityksessä sekä haastattelemalla yhdeksän suomalaisen sähkönmyyntiyhtiön henkilöitä riskienhallinnan haasteiden sekä tietojärjestelmien näkökulmasta. Saatavilla olevien tietojen nykyistä parempi hyödyntäminen ja automatisointi voivat auttaa pienentämään yhtiöiden riskitasoa ja parantaa menestymisen edellytyksiä sähkönmyynnin vähittäismarkkinoilla. Lisäksi kulloiseenkin markkinatilanteeseen sopivat sähkön hankintahinnan suojausstrategiat sekä monipuoliset dynaamiset hinnoittelumallit auttavat pienentämään yhtiön kokemia riskejä tai niiden vaikutuksia. Näiden hyödyntäminen vaatii laajaa ymmärrystä sähkö- ja johdannaismarkkinoiden toiminnasta sekä usein myös nykyisten tietojärjestelmien kehittämistä. Tulevaisuudessa yhä yleistyvä hajautettu tuotanto sekä kysynnän jousto asettavat tietojärjestelmille uusia vaatimuksia, jotka toteutuessaan mahdollistavat uudenlaisten palveluiden käyttöönoton sekä voivat tuoda tilaa myös alan uusille toimijoille. Työssä käsitellään energiayhtiöiden kokemia riskejä sähkönmyynnin näkökulmasta, esitellään alan yleisimmät riskit sekä keinot ja työkalut niiltä suojautumiseen. Työn lopuksi tarkastellaan sähkönmyynnin ja –hankinnan oleellisimpia prosesseja riskienhallinnan kehittämisen näkökulmasta.

Learning in peer-to-peer markets: evidence from Airbnb

Peer-to-peer markets are highly uncertain environments due to the constant presence of shocks. As a consequence, sellers have to constantly adjust to these shocks. Dynamic Pricing is hard, especially for non-professional sellers. We study it in an accommodation rental marketplace, Airbnb. With scraped data from its website, we: 1) describe pricing patterns consistent with learning; 2) estimate a demand model and use it to simulate a dynamic pricing model. We simulate it under three scenarios: a) with learning; b) without learning; c) with full information. We have found that information is an important feature concerning rental markets. Furthermore, we have found that learning is important for hosts to improve their profits.

Análise de volatilidade, integração de preços e previsibilidade para o mercado brasileiro de camarão

The present paper has the purpose of investigate the dynamics of the volatility structure in the shrimp prices in the Brazilian fish market. Therefore, a description of the initial aspects of the shrimp price series was made. From this information, statistics tests were made and selected univariate models to be price predictors. Then, it was verified the existence of relationship of long-term equilibrium between the Brazilian and American imported shrimp and if, confirmed the relationship, whether or not there is a causal link between these assets, considering that the two countries had presented trade relations over the years. It is presented as an exploratory research of applied nature with quantitative approach. The database was collected through direct contact with the Companhia de Entrepostos e Armazéns Gerais de São Paulo (CEAGESP) and on the official website of American import, National Marine Fisheries Service - National Oceanic and Atmospheric Administration (NMFS- NOAA). The results showed that the great variability in the active price is directly related with the gain and loss of the market agents. The price series presents a strong seasonal and biannual effect. The average structure of price of shrimp in the last 12 years was R$ 11.58 and external factors besides the production and marketing (U.S. antidumping, floods and pathologies) strongly affected the prices. Among the tested models for predicting prices of shrimp, four were selected, which through the prediction methodologies of one step forward of horizon 12, proved to be statistically more robust. It was found that there is weak evidence of long-term equilibrium between the Brazilian and American shrimp, where equivalently, was not found a causal link between them. We concluded that the dynamic pricing of commodity shrimp is strongly influenced by external productive factors and that these phenomena cause seasonal effects in the prices. There is no relationship of long-term stability between the Brazilian and American shrimp prices, but it is known that Brazil imports USA production inputs, which somehow shows some dependence productive. To the market agents, the risk of interferences of the external prices cointegrated to Brazilian is practically inexistent. Through statistical modeling is possible to minimize the risk and uncertainty embedded in the fish market, thus, the sales and marketing strategies for the Brazilian shrimp can be consolidated and widespread

An incentivized auction based group-selling approach for demand response management in V2G systems

Vehicle-to-Grid (V2G) system with efficient Demand Response Management (DRM) is critical to solve the problem of supplying electricity by utilizing surplus electricity available at EVs. An incentivilized DRM approach is studied to reduce the system cost and maintain the system stability. EVs are motivated with dynamic pricing determined by the group-selling based auction. In the proposed approach, a number of aggregators sit on the first level auction responsible to communicate with a group of EVs. EVs as bidders consider Quality of Energy (QoE) requirements and report interests and decisions on the bidding process coordinated by the associated aggregator. Auction winners are determined based on the bidding prices and the amount of electricity sold by the EV bidders. We investigate the impact of the proposed mechanism on the system performance with maximum feedback power constraints of aggregators. The designed mechanism is proven to have essential economic properties. Simulation results indicate the proposed mechanism can reduce the system cost and offer EVs significant incentives to participate in the V2G DRM operation.

Essays on Omnichannel Sale

Thesis (Ph.D.)--University of Washington, 2016-08

Análise de volatilidade, integração de preços e previsibilidade para o mercado brasileiro de camarão

The present paper has the purpose of investigate the dynamics of the volatility structure in the shrimp prices in the Brazilian fish market. Therefore, a description of the initial aspects of the shrimp price series was made. From this information, statistics tests were made and selected univariate models to be price predictors. Then, it was verified the existence of relationship of long-term equilibrium between the Brazilian and American imported shrimp and if, confirmed the relationship, whether or not there is a causal link between these assets, considering that the two countries had presented trade relations over the years. It is presented as an exploratory research of applied nature with quantitative approach. The database was collected through direct contact with the Companhia de Entrepostos e Armazéns Gerais de São Paulo (CEAGESP) and on the official website of American import, National Marine Fisheries Service - National Oceanic and Atmospheric Administration (NMFS- NOAA). The results showed that the great variability in the active price is directly related with the gain and loss of the market agents. The price series presents a strong seasonal and biannual effect. The average structure of price of shrimp in the last 12 years was R$ 11.58 and external factors besides the production and marketing (U.S. antidumping, floods and pathologies) strongly affected the prices. Among the tested models for predicting prices of shrimp, four were selected, which through the prediction methodologies of one step forward of horizon 12, proved to be statistically more robust. It was found that there is weak evidence of long-term equilibrium between the Brazilian and American shrimp, where equivalently, was not found a causal link between them. We concluded that the dynamic pricing of commodity shrimp is strongly influenced by external productive factors and that these phenomena cause seasonal effects in the prices. There is no relationship of long-term stability between the Brazilian and American shrimp prices, but it is known that Brazil imports USA production inputs, which somehow shows some dependence productive. To the market agents, the risk of interferences of the external prices cointegrated to Brazilian is practically inexistent. Through statistical modeling is possible to minimize the risk and uncertainty embedded in the fish market, thus, the sales and marketing strategies for the Brazilian shrimp can be consolidated and widespread

Análise de volatilidade, integração de preços e previsibilidade para o mercado brasileiro de camarão

The present paper has the purpose of investigate the dynamics of the volatility structure in the shrimp prices in the Brazilian fish market. Therefore, a description of the initial aspects of the shrimp price series was made. From this information, statistics tests were made and selected univariate models to be price predictors. Then, it was verified the existence of relationship of long-term equilibrium between the Brazilian and American imported shrimp and if, confirmed the relationship, whether or not there is a causal link between these assets, considering that the two countries had presented trade relations over the years. It is presented as an exploratory research of applied nature with quantitative approach. The database was collected through direct contact with the Companhia de Entrepostos e Armazéns Gerais de São Paulo (CEAGESP) and on the official website of American import, National Marine Fisheries Service - National Oceanic and Atmospheric Administration (NMFS- NOAA). The results showed that the great variability in the active price is directly related with the gain and loss of the market agents. The price series presents a strong seasonal and biannual effect. The average structure of price of shrimp in the last 12 years was R$ 11.58 and external factors besides the production and marketing (U.S. antidumping, floods and pathologies) strongly affected the prices. Among the tested models for predicting prices of shrimp, four were selected, which through the prediction methodologies of one step forward of horizon 12, proved to be statistically more robust. It was found that there is weak evidence of long-term equilibrium between the Brazilian and American shrimp, where equivalently, was not found a causal link between them. We concluded that the dynamic pricing of commodity shrimp is strongly influenced by external productive factors and that these phenomena cause seasonal effects in the prices. There is no relationship of long-term stability between the Brazilian and American shrimp prices, but it is known that Brazil imports USA production inputs, which somehow shows some dependence productive. To the market agents, the risk of interferences of the external prices cointegrated to Brazilian is practically inexistent. Through statistical modeling is possible to minimize the risk and uncertainty embedded in the fish market, thus, the sales and marketing strategies for the Brazilian shrimp can be consolidated and widespread